Exploring the Structural Relationships among AI Tool Use, Learner Agency, and Creativity in Elementary Music Education

This study examined the structural relationships among AI tool use, learner agency, and music creativity in elementary students. A total of 178 participants responded to a survey designed to measure perceived usefulness, perceived ease of use, intention to use AI tools, components of learner agency, and dimensions of musical creativity. Confirmatory factor analysis (CFA) was conducted to verify the validity of the measurement model, and structural equation modeling (SEM) was employed to test the research hypotheses. The CFA results supported convergent validity for all major constructs; however, discriminant validity was not fully established for several subfactors of learner agency and musical creativity. The structural model showed an acceptable level of fit. The SEM results indicated that AI tool use had a significant positive effect on learner agency, and learner agency strongly predicted music creativity. AI tool use also demonstrated a significant direct effect on music creativity. In addition, the indirect effect of AI tool use on music creativity through learner agency was statistically significant, confirming that learner agency serves as a partial mediator between AI tool use and music creativity. These findings suggest that AI-supported learning environments can foster both learner agency and creative musical expression in elementary students. The study highlights the importance of integrating AI tools with pedagogical approaches that enhance learner autonomy and creative engagement.